Dunsin on Journalists Hangout Narrates the Indepth of Data Governance

Please let us meet you.

My name is Dunsin Opebiyi, a data governance expert with over five years of experience spanning diverse sectors such as facility management, healthcare, Edtech, SAAS and finance. Before transitioning into data governance, I built a solid foundation with over eight years of combined experience in finance and project analysis, as well as serving as a relationship manager in the banking industry.

As a data governance professional, my core focus is on crafting and executing data strategies that ensure regulatory compliance while enhancing business efficiency. This includes establishing robust policies and frameworks to manage data quality, security, and accessibility. I ensure that data is accurate, aligned with regulatory standards like GDPR, and accessible to the right stakeholders at the right time. My role involves collaborating with cross-functional teams to integrate governance practices with business objectives, enabling data-driven decision-making and helping organizations harness data as a strategic asset.

Additionally, I am the co-founder of an EdTech and mentoring platform designed to support young professionals in overcoming data management challenges. As a passionate advocate for data and digital technology, I am actively engaged in the digital tech ecosystem in both the UK and Nigeria. I frequently speak at industry conferences on topics such as data protection, governance, and AI

Can you explain what data governance means in simple terms and why it’s essential for businesses today?

Data governance refers to managing and controlling an organization’s data to ensure it is accurate, consistent, secure, and compliant with regulations. In simple terms, it’s about putting rules and guidelines in place to manage data responsibly.
For businesses, data governance is essential because it turns data into a reliable asset that drives decision-making. In today’s digital world, organizations are dealing with massive amounts of data, and without proper governance, this data can become inconsistent or even risky to use. Good governance ensures that the right people have access to the right data, while protecting sensitive information and adhering to laws like GDPR or Nigeria’s Data Protection Regulation (NDPR).

Beyond compliance, it also optimizes business operations. With reliable, well-governed data, businesses can make smarter decisions faster, reduce operational inefficiencies, and minimize risks related to data breaches or misuse. Essentially, data governance allows businesses to fully unlock the value of their data while ensuring it’s used responsibly.

How does data governance impact business decision-making and operational efficiency?

Data governance plays a crucial role in both business decision-making and operational efficiency. When data is well-governed, it’s reliable, consistent, and accessible, allowing leaders to make informed decisions quickly. Without a strong governance framework, decision-makers might be working with incomplete or inaccurate data, which can lead to poor business outcomes.

For example, in a well-governed environment, data is cleaned, validated, and structured. This means that when a manager needs to analyse sales trends or customer behavior, they can trust the data is correct and up-to-date. This level of trust reduces the risk of errors in strategy formulation or execution.

In terms of operational efficiency, data governance eliminates inefficiencies that arise from poor data management. For instance, when teams across departments have access to standardized and high-quality data, they can work faster and more collaboratively. Instead of wasting time searching for or cleaning data, teams can focus on productive tasks like innovation or improving customer experiences.

Furthermore, by implementing clear data governance policies, businesses can automate certain compliance processes, saving time and resources that would otherwise go into manual checks or error corrections. This not only boosts efficiency but also reduces operational risks, such as penalties from non-compliance with data privacy regulations like GDPR or NDPR.

In summary, data governance ensures that businesses can make better, faster decisions, while improving overall operational efficiency by minimizing data-related risks and inefficiencies. It’s about turning data into a trusted and valuable resource for the entire organization.

What are some of the key challenges organizations face when implementing data governance frameworks in Nigeria?

When implementing data governance frameworks in Nigeria, organizations face several key challenges, and it’s something I’ve seen firsthand.
One major challenge is awareness. Many companies still don’t fully understand the importance of data governance, so it can be tough to get buy-in from top management and staff. Often, they view it as a regulatory burden rather than a strategic asset.

Another challenge is data silos. Many organizations in Nigeria still have fragmented systems where data is stored in different places, whether it’s different departments or systems that don’t talk to each other. This makes it difficult to standardize and manage data across the organization.

Compliance with local and international regulations, like Nigeria’s Data Protection Regulation (NDPR) and GDPR, can also be quite complex. Many organizations struggle to keep up with evolving regulations, especially if they don’t have the right legal or technical resources.
And let’s not forget resource constraints. Smaller businesses, in particular, often lack the financial and technological resources to fully invest in data governance tools and infrastructure, not to mention the lack of experienced data governance professionals.

Then there’s cultural resistance. Implementing a data governance framework requires changing how people work with data. Teams often resist these changes because they see governance as additional bureaucracy. Overcoming this mindset and building a culture of data stewardship requires strong leadership and continuous education.

However, despite these challenges, the value of data governance is immense. When done right, it transforms data into a strategic asset, improving decision-making, ensuring compliance, and unlocking business growth.

How do you ensure compliance with regulations like GDPR and Nigeria’s Data Protection Regulation (NDPR)?

Ensuring compliance with regulations like GDPR and Nigeria’s Data Protection Regulation (NDPR) is a structured, multi-step process.
First, I start by conducting a data audit. This helps identify the personal data we collect, how it’s processed, and where it’s stored. Knowing this is crucial for adhering to regulations, as it helps track the entire data lifecycle.

Next, I implement privacy-by-design principles. This means integrating data protection into every phase of a project, whether it’s building a new system or launching a product. Privacy isn’t an afterthought; it’s embedded from the start.

Another important step is creating clear policies and training. I ensure that staff across all departments are educated on data privacy, their responsibilities, and how to handle data in compliance with these regulations. Regular training sessions keep everyone informed about updates in GDPR or NDPR laws.
Consent management is also key. We ensure that users know what data we’re collecting, how it will be used, and that we get their explicit consent before processing their personal information. This is critical under both GDPR and NDPR regulations.

Lastly, I use data access controls and encryption to protect sensitive data. This includes defining who has access to certain types of data and ensuring that personal data is protected from unauthorized access. Regular audits and risk assessments help to maintain ongoing compliance.

In summary, compliance is about being proactive and putting the right structures in place, educating teams, and continuously monitoring for any changes in the regulatory landscape. That way, we’re always ahead of the curve when it comes to protecting data and adhering to the laws.

What role does data governance play in managing data privacy and security risks?

Data governance plays a crucial role in managing data privacy and security risks by providing a structured framework to handle data responsibly. At its core, it’s about ensuring that sensitive data is properly managed, accessed, and protected.

For data privacy, governance sets the rules around how personal data is collected, processed, and shared. This is essential for compliance with regulations like GDPR and Nigeria’s NDPR, ensuring that organizations respect individuals’ rights and manage consent properly.
When it comes to security risks, data governance helps organizations identify vulnerabilities by controlling who has access to data, how it is stored, and how it’s transmitted. For example, a well-defined governance framework includes access control policies, ensuring only authorized individuals can view or manipulate sensitive data. It also enforces the use of security measures such as encryption and regular audits to catch potential issues before they escalate.
In practice, data governance doesn’t just protect data but fosters transparency and accountability across the organization. With clear policies in place, everyone knows how to handle data responsibly, which drastically reduces the likelihood of breaches or privacy violations. Ultimately, data governance is about managing risk proactively, protecting both the organization and the people whose data is being handled.

How do you approach creating a data governance strategy tailored to an organization’s needs?

When creating a data governance strategy tailored to an organization’s needs, the first step is understanding the specific goals and challenges the organization faces. I start with a data audit to map out where data is stored, how it flows, and who uses it. This helps identify gaps or risks, whether in compliance, quality, or accessibility.
Next, I work with key stakeholders across departments to ensure the strategy aligns with both business objectives and regulatory requirements. For example, if the company operates in finance or healthcare, regulatory compliance will be a top priority. On the other hand, in sectors like retail or tech, data analytics for customer insights might be more critical.

I then develop policies and frameworks for data management, focusing on data quality, security, access control, and compliance. Each element of the strategy is tailored to the specific industry regulations and organizational structure. For example, if the company has a decentralized data landscape, I might focus more on data standardization.
Finally, the strategy isn’t static. I implement regular audits and reviews to ensure the governance framework evolves as the business grows or as regulations change. I also prioritize training and communication, making sure everyone in the organization understands their role in maintaining data governance standards.
This holistic, tailored approach ensures that data governance becomes a value-driving aspect of the organization, enhancing decision-making, reducing risks, and ensuring compliance.

How do you measure the success of a data governance initiative? What metrics do you focus on?

To measure the success of a data governance initiative, I focus on both qualitative and quantitative metrics. One key metric is data quality, where we look at the accuracy, consistency, and completeness of data. This can be measured through data quality scores, showing how reliable the data is for decision-making.

Another critical metric is compliance rates. This measures how well the organization is adhering to regulations like GDPR or NDPR. Regular audits help track this.
I also pay attention to user engagement, ensuring that teams are adopting data governance tools and processes. The more teams engage with governance, the more embedded it becomes in daily operations.

Finally, I measure risk reduction. This includes tracking a decline in data breaches or errors. When data-related incidents decrease, it’s a clear sign that governance is working effectively. These metrics together give a full picture of how governance is driving value and ensuring data integrity across the organization.

In your experience, how can organizations overcome resistance to data governance initiatives from stakeholders?

In my experience, resistance to data governance initiatives usually stems from a fear of change or a misunderstanding of its benefits. To overcome this, I start by communicating the value of governance clearly, emphasizing how it supports better decision-making, reduces risks, and improves data quality.

Involving key stakeholders early is essential. By getting their input and addressing their concerns upfront, they feel more invested in the process. I also aim for quick wins. These are often the small, visible successes that show the immediate benefits of data governance. These help build trust and demonstrate that governance isn’t just about compliance; it’s about empowering teams with reliable data.

Another key factor is continuous training. Often, resistance comes from a lack of understanding. By providing training sessions and open channels for feedback, I make sure teams feel supported and informed. This creates a culture of data stewardship where governance is seen as an enabler, not a burden.

How has the rapid growth of cloud computing and AI impacted data governance practices?

The rapid growth of cloud computing and AI has transformed data governance in significant ways. First, with data moving to the cloud, organizations face the challenge of maintaining data security and privacy across decentralized platforms. This has led to an increased focus on access control, encryption, and ensuring that data in the cloud complies with global regulations like GDPR and NDPR.

In terms of AI, governance now includes managing the ethical use of data in machine learning models. Ensuring data quality, reducing bias, and establishing data transparency are critical in preventing unintended consequences from AI-driven decisions. These technological advancements have forced data governance to become more agile and adaptive, with policies designed to handle rapid innovation while safeguarding data integrity
In essence, the rise of cloud and AI requires governance frameworks that not only protect data but also enable organizations to leverage these technologies safely and effectively.
 
What tools and technologies do you recommend for managing data quality and governance?

Technology plays a vital role in implementing effective data governance practices. Data governance tools help organizations catalog their data assets, track data lineage, and ensure compliance with regulations. They enable businesses to maintain high data quality standards while providing visibility into data usage.
When it comes to managing data quality and governance, there are some fantastic tools I recommend based on my experience.

Collibra stands out for its comprehensive data governance capabilities, helping organizations track their data assets and maintain compliance. Then there’s Informatica, which is great for ensuring data quality through profiling and monitoring.
Talend is another excellent option, especially if you’re looking for open-source flexibility in data integration. For visualizing data quality, I often suggest Tableau or Power BI.

Lastly, if you’re automating workflows, Apache Airflow is a strong choice. Ultimately, the best tool really depends on your organization’s specific needs, but these are solid options to consider.
It is also necessary that strategies and needs should drive technology and not the other way around. At the end of the day, tools and technology are enablers, so the need drives the technology required.

What advice would you give to companies in Nigeria just starting their data governance journey?

For companies in Nigeria just starting their data governance journey, my advice is to start small but think big. Define clear goals that align with your overall business strategy. Engage stakeholders from the beginning to foster a culture of data stewardship—it’s essential that everyone understands their role in managing data responsibly.

Invest in the right tools and technologies, but also focus on training your team to ensure they’re equipped to handle data governance effectively. Lastly, be prepared to iterate and adapt your governance framework as your organization grows and evolves. This flexibility will help you navigate the dynamic landscape of data management successfully.

How do you see the future of data governance evolving in Nigeria, particularly in light of growing digital transformation?

I see the future of data governance in Nigeria evolving dramatically, particularly as organizations accelerate their digital transformation efforts. As businesses increasingly adopt technologies like cloud computing, AI, and big data analytics, the need for effective data governance will become paramount.

This means we’ll likely see a stronger focus on establishing clear data governance frameworks that ensure compliance with regulations like NDPR while also promoting data quality and security. Additionally, organizations will need to invest in training their staff, as data literacy will be crucial for navigating this evolving landscape.

Furthermore, as data becomes a central asset in driving business decisions, organizations that prioritize data governance will gain a competitive edge. They’ll be able to leverage data more effectively, enhance decision-making, and build trust with customers by demonstrating responsible data management practices.
Ultimately, I envision a future where data governance is not just about compliance but is viewed as a strategic enabler for growth and innovation in Nigeria. As companies recognize the importance of governance, we’ll likely see more collaboration among sectors to establish best practices and standards, fostering a healthier data ecosystem overall.

How can organizations in Nigeria effectively create a culture of data stewardship among employees?

Creating a culture of data stewardship among employees in Nigeria starts with leadership buy-in. When leaders prioritize data governance and demonstrate its importance, it sets the tone for the entire organization.
Next, organizations should invest in training and education. By providing workshops and resources that emphasize the value of accurate data management, employees become more aware of their roles in safeguarding data.

Additionally, fostering open communication about data practices and encouraging feedback creates a collaborative environment. Recognizing and rewarding employees who actively engage in data stewardship can also reinforce these behaviors, making data governance a shared responsibility rather than a top-down directive.

What are the most common pitfalls you see companies encountering during their data governance implementations?

When it comes to data governance implementations, several common pitfalls often trip up companies. One major challenge is the lack of clear objectives. Without well-defined goals, it becomes difficult to measure success or align data governance efforts with business needs.
Another common issue is insufficient stakeholder engagement.

When key stakeholders aren’t involved from the outset, it can lead to resistance or a lack of buy-in across departments. This often results in a governance framework that doesn’t resonate with those who need to implement it.
Additionally, many organizations underestimate the importance of training and communication. If employees are not educated about data governance practices, they may not understand their roles, leading to gaps in compliance and data quality.

Lastly, a frequent pitfall is trying to implement data governance as a one-time project rather than an ongoing process. Data governance should evolve with the organization, adapting to changes in technology and regulations. By recognizing these common pitfalls and proactively addressing them, companies can set themselves up for a successful data governance journey.

What do you consider a success in Data Governance

Success in data governance, for me, goes beyond rigid rules, policies, or processes. It’s about cultivating an environment where data is accurate, trusted, and valuable across the entire organization. Ultimately, it’s about embedding a culture where data is treated as a strategic asset, and every team recognizes the importance of secure, compliant, and high-quality data. In this ecosystem, governance isn’t seen as a hurdle but as an enabler of better decisions and business outcomes.

Success begins with clear policies and standards governing how data is collected, stored, and utilized. These policies ensure data quality; a critical aspect of governance. If your data isn’t reliable, even the most sophisticated analytics or AI systems will fall short. When teams across the organization can consistently trust the data they’re using to make decisions, it’s a strong sign that the governance framework is doing its job.
Another pillar of success is regulatory compliance. In a landscape shaped by laws like GDPR and CCPA, managing data in a compliant manner is not only necessary to avoid penalties but also to build trust with customers and stakeholders. A successful governance framework ensures data privacy and protection, enhancing your organization’s reputation and instilling confidence.
Equally important is stakeholder engagement. Successful governance isn’t just about policies, it’s about collaboration. I actively involve key stakeholders, such as IT, marketing, and legal, from the outset to ensure everyone understands their role in data stewardship. When teams actively participate in governance initiatives, it creates shared responsibility and strengthens the integrity and usage of data.

Data governance must also be adaptable. As new technologies like AI emerge and business models evolve, a successful governance framework remains flexible, allowing it to scale and adjust to new challenges.
In short, successful data governance is a collaborative, evolving process that empowers teams to use data responsibly while supporting organizational goals. It ensures data drives real business value, creating a sustainable competitive advantage.

How does data governance enhance customer trust and engagement in today’s digital landscape?

Data governance plays a vital role in enhancing customer trust and engagement in today’s digital landscape. When organizations prioritize strong data governance practices, they demonstrate a commitment to protecting customer data and ensuring compliance with regulations. This builds trust with customers, as they feel confident that their personal information is handled responsibly.
Moreover, effective data governance leads to better data quality, which means that businesses can offer more personalized and relevant experiences. When customers see that a company understands their needs and preferences, they are more likely to engage positively and remain loyal.

Additionally, transparent data practices, like clear consent mechanisms and easy access to personal data, further enhance customer trust. In a world where data breaches are all too common, organizations that actively promote and uphold strong governance standards stand out, fostering lasting relationships with their customers.

What role does leadership play in the success of data governance initiatives within an organization?

Leadership is absolutely crucial for the success of data governance initiatives within an organization. When leaders prioritize data governance, they set the tone from the top, making it clear that managing data responsibly is a key organizational objective. This kind of commitment fosters a culture of accountability, where everyone understands the importance of data stewardship.

Moreover, effective leaders actively engage with stakeholders at all levels. They ensure that employees know their roles in governance efforts, which helps break down silos and promotes collaboration across departments. When leadership communicates the value of data governance; like improved decision-making and risk mitigation, it encourages teams to embrace these initiatives rather than see them as just another compliance burden.

Additionally, leaders must be visible advocates for data governance, participating in training sessions and discussions about data practices. Their involvement not only demonstrates the significance of data governance but also encourages employees to adopt these practices in their daily work.
Ultimately, strong leadership creates an environment where data governance is not just a top-down directive but a shared responsibility, driving lasting change and ensuring that data is viewed as a valuable asset for the organization.

How can businesses balance the need for data access with the necessity of data security?

Balancing the need for data access with the necessity of data security is crucial for any business today. It starts with establishing a clear data governance framework that defines who has access to what data and under what circumstances.
Organizations can implement role-based access controls, allowing employees to access only the data necessary for their specific roles. This approach not only secures sensitive information but also empowers teams with the data they need to make informed decisions.

Regular training and awareness programs are essential. Employees should understand the importance of data security and how to handle sensitive information properly. By fostering a culture of responsibility, organizations can ensure that data is both accessible and secure.
Ultimately, leveraging technology, such as encryption and monitoring tools, can provide an additional layer of protection. This way, businesses can maintain the agility and accessibility they need while safeguarding their data from unauthorized access or breaches. It’s about creating a balanced approach that prioritizes both innovation and security.

What are some emerging trends in data governance that Nigerian businesses should be aware of?

Firstly, the rise of cloud-based solutions is transforming how organizations manage and store their data. As more companies migrate to the cloud, data governance frameworks must evolve to address security and compliance in these new environments.

Another trend is the increasing importance of data privacy regulations. With the implementation of laws like the Nigeria Data Protection Regulation (NDPR), businesses must prioritize compliance to avoid hefty fines and protect customer trust.

Additionally, the integration of AI and machine learning in data governance processes is becoming more common. These technologies can help automate data quality assessments and identify potential risks, making governance more efficient and proactive.

Finally, there’s a growing focus on data literacy within organizations. Ensuring that employees understand the importance of data governance and their role in it is crucial for fostering a culture of accountability and stewardship.
By staying ahead of these trends, Nigerian businesses can enhance their data governance practices, safeguard sensitive information, and leverage data as a strategic asset for growth.

What is the importance of stakeholder involvement in developing and maintaining data governance policies?

Stakeholder involvement in developing and maintaining data governance policies is absolutely crucial. First, it ensures that the policies reflect the needs and perspectives of different departments within the organization. Each team; whether it’s IT, marketing, or compliance has unique insights about how data is used, and their input helps create a more comprehensive governance framework.
Involving stakeholders also fosters a sense of ownership and accountability. When employees feel that they have a voice in the governance process, they are more likely to engage with the policies and adhere to them. This buy-in is essential for the successful implementation of data governance practices.

Moreover, regular collaboration with stakeholders helps keep the governance policies relevant and adaptable to changing business needs. As the organization evolves, having a diverse group of stakeholders ensures that policies can be updated and refined to address new challenges or opportunities. Ultimately, involving stakeholders leads to more effective data governance that aligns with the organization’s goals and enhances overall data quality and compliance.

How do you foresee the impact of data governance on business intelligence and analytics in the Nigerian market?

I foresee that data governance will profoundly impact business intelligence and analytics in the Nigerian market, primarily by enhancing the quality and trustworthiness of data used for decision-making.
As organizations adopt more advanced analytics tools, effective governance ensures that the data feeding these tools is accurate and consistent. This is crucial for generating reliable insights, which can lead to better strategic decisions. With a strong governance framework, companies can also ensure compliance with local regulations, which builds trust with customers and stakeholders.

Moreover, improved data governance facilitates cross-departmental collaboration. When teams know they can rely on high-quality data, they’re more likely to share insights and work together on analytics initiatives. This culture of collaboration can drive innovation and efficiency, allowing businesses to respond more swiftly to market changes.
In Nigeria, where businesses are increasingly leveraging data to stay competitive, strong data governance will be a key differentiator. Organizations that invest in solid governance practices will not only enhance their analytics capabilities but will also position themselves as leaders in a data-driven economy. This ultimately fosters a more informed decision-making process and drives sustainable growth across various sectors.

What advice do you have for those aspiring to get into data governance

If you’re looking to get into data governance, the first thing I’d say is to really get a solid grasp of the core principles. You’ve got to understand things like data quality, data security and privacy, and compliance regulations. Frameworks like DAMA-DMBOK are super helpful as they give you a structured approach to data management. Also, be familiar with regulations like GDPR if you’re in Europe, or NDPR if you’re dealing with Nigeria. These are the basics you’ll need as you move forward in your career.

And you can’t overlook the technical side of things. I always say having some technical know-how is a big plus. Learn about the tools used in data governance, like data catalogs, data lineage tools, and platforms for data quality. You don’t need to be an engineer, but a basic understanding of data management, storage, and design will really help when you’re working with technical teams. It helps you communicate better and bridge the gap between governance and tech.
But remember, data governance isn’t just about regulations or the framwork. Soft skills are very important. You’ll need to be a great communicator, especially when working with cross-functional teams. Being able to explain the importance of data governance to non-technical stakeholders is key. Plus, networking is huge, both within your organization and in the broader data community. It’ll open up opportunities and keep you learning.
Speaking of learning, the field is always evolving, especially with new technologies like AI shaking things up. Stay on top of industry trends, subscribe to publications, follow experts on LinkedIn, and join relevant groups. It’s an exciting space, but it means you’ve got to keep learning. That’s what makes it so dynamic.

I’d also recommend finding a mentor. Honestly, having someone guide you who’s been through the challenges you’re facing can be invaluable. They’ll offer insights, share their experiences, and help you navigate your career. Look for mentorship opportunities, whether formal or just by connecting with someone you admire in the field.

Lastly, getting practical experience is a must. Even if it’s through internships or volunteering, hands-on experience will teach you more than any book can. Look for roles where you can get involved with data governance tasks like data quality assessments, compliance audits, or stewardship initiatives. It’s those projects that really bring the theory to life.
Data governance might sound like a lot of rules and regulations, but at its core, it’s about empowering organizations to make smarter, data-driven decisions. If you can keep that in mind, the work becomes much more rewarding